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Key takeaways:
- More than systems of record, ERP and HCM are becoming the foundation for orchestrating intelligent work. As AI and agents are embedded into workflows, you should revisit not just process design but where work sits, who performs it, and how decisions get made.
- The value of intelligent ERP and HCM depends on operating model choices. The technology can enable new automation, agentic work, and managed services, but value comes when you deliberately decide what to own, what technology should perform, and where human talent should focus.
- ERP/HCM transformation has direct talent-strategy implications. As work shifts across teams, AI agents, and managed service employees, you may need to rethink roles, skills, career paths, rewards, redeployment, and change management—not simply train people on a new system.
As our recent perspective “Why ERP matters more in the age of AI” explained, enterprise resource planning (ERP) is becoming more important as organizations scale AI. ERP provides the trusted data, transactions, controls, governance, and workflows that can help make AI-driven outcomes achievable, auditable, and scalable.
That foundation is critical. But it also raises an important question: What happens to the organization operating on top of it?
As ERP and human capital management (HCM) platforms become more intelligent, AI is increasingly embedded into workflows. Agents can interpret information, recommend actions, and, in some cases, execute work. Insights are provided at the point of decision, while processes that once relied on multiple manual interventions can increasingly be orchestrated across people and technology.
That creates new choices not only about systems and processes but about where work happens, who—or what—performs it, how decisions get made, and where people create the greatest value. Technology creates the potential. The operating model determines how much of that value is realized.
Intelligent technology creates new operating model choices
ERP and HCM programs have long required organizations to decide what to standardize, automate, and centralize. AI expands the possibilities considerably.
Many existing processes and structures were designed around constraints that are now changing. Information was difficult to access, analysis required specialized resources, systems were disconnected, and transactions required significant manual intervention. If organizations can remove these constraints, they’ll be able to rethink the work itself.
That brings fundamental operating model choices into view: where work should live, where decisions should sit, what should remain differentiated, and, increasingly, who or what should perform the work. The future workforce increasingly includes three types of workers—human employees, AI agents, and managed service employees—and leaders need to decide deliberately where work belongs.
- Human employees may focus on activities requiring judgment, relationships, creativity, and accountability.
- AI agents can increasingly execute, coordinate, or augment work at speed and scale.
- Managed services create another choice entirely. Organizations may decide that certain processes don’t need to be internal at all.
A finance organization, for instance, may spend less time gathering and reconciling information and more time advising the business. HR may shift capacity from transactions to workforce insights and talent decisions. Supply chain teams may focus less on routine monitoring and more on exceptions and trade-offs. In other areas, the bigger question may be whether or not the organization needs to maintain the underlying delivery capability internally.
The result isn’t just a new tech-enabled operating model but a new workforce equation. What should the enterprise own, what should technology perform, what should be delivered through managed services, and where can human talent create greater value?
Operating model choices require a new talent strategy
Once you make these choices, the next question is what they mean for the workforce. If people are doing different work or working alongside agents and managed service employees, the implications extend well beyond individual tasks. Organizations may need different roles, different capabilities, and different ways of selecting, developing, deploying, and rewarding talent.
That’s where business and technology leaders should engage the office of the CHRO to shape the talent strategy that makes the new operating model work. Decisions about how work will be delivered should connect directly to decisions about the workforce that will deliver it. In other words, once your operating model changes, your talent strategy should too.
As evidence of that talent shift, PwC’s 2026 Global AI Jobs Barometer found that the skills required in the most AI-exposed jobs are changing more than twice as fast as in the least AI-exposed jobs. Even entry-level roles are changing. Those most exposed to AI are seven times more likely to require traditionally senior skills such as judgment and leadership.
Evolving your talent strategy could involve rewriting job descriptions as responsibilities change. Learning will need to go beyond system proficiency to help employees build the skills to work differently and interact effectively with AI and agents.
Organizations should rethink how they select talent and where they can redeploy existing employees as capacity is released. The implications can extend further into the talent system.
- Career paths may need to change as traditional tasks and role boundaries shift.
- Performance measures and rewards may need to reflect new forms of contribution.
- Compensation may need to evolve as certain roles become more judgment-intensive, technology-enabled, or focused on orchestrating work across people, agents, and providers.
These aren’t isolated HR decisions or downstream adoption issues. They’re part of a talent strategy that makes the operating model viable.
Change management’s mandate is expanding
Communications, training, stakeholder engagement, and adoption remain important. But when a transformation changes not only the system but also roles, decision rights, and how work gets done, the change agenda has to go further.
Change management increasingly becomes the bridge between designing the new operating model and making it real. Beyond just using new technology, leaders and employees need to understand how expectations, interactions, and ways of working are changing and what they need to do differently as a result.
This means embracing change earlier and connecting it more closely with technology, process, operating model, and talent decisions. The goal isn’t simply readiness for go-live but helping the organization transition to and sustain the new way of operating.
Designing for continuous change
The future state may not stay “future” for very long. Cloud platforms, AI capabilities, agents, and managed service models are evolving quickly. That means even a recently designed operating model may already be outdated.
For organizations that have just completed or are still completing a major ERP or HCM transformation, the instinct may be to let the new environment settle. But a recent implementation isn’t necessarily a reason to wait. It may be a reason to look again. What is possible now that wasn’t when the future state was designed? What should be automated or augmented next? What should remain internal, and what may be better delivered as a service?
The operating model can no longer be treated as a one-time design exercise. One of the defining capabilities of the intelligent enterprise is the ability to continually revisit how work gets done as the possibilities change.
The fundamental truth about tech transformation hasn’t changed, but what it means to enable people has
Successful tech transformations have always depended on people, and that’s still true. The best digital core can’t deliver its entire value if the organization doesn’t adopt it, use it, and change how work gets done around it.
In an intelligent enterprise, preparing the workforce could mean redefining their roles, equipping them to work alongside agents, building new skills, creating different career paths and rewards, redeploying capacity, and preparing leaders to manage work delivered across employees, technology, and external providers.
That’s why the operating model and talent strategy shouldn’t sit downstream from technology transformation. They’re part of how organizations turn the capabilities of their digital core into business value.
The digital core is critical. The technology possibilities are expanding rapidly. The big question now is whether your organization and its people are ready to capture everything that technology makes possible.
Activate talent. Accelerate impact.
Empower your workforce to fuel business performance
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